Many thanks to Marco Ruscone and Laurence Calzone for all their work that went into this tutorial, and to Andrea Checcoli, @rheiland.bsky.social, Emmanuel Barillot, @mathcancer.bsky.social for helping us build, test, write, and review everything! Feedback welcome !

To conclude, this tutorial shows that #PhysiBoSS modeling doesn't require C++ coding skills, and is now simpler thanks to #PhysiCell Studio (even for advanced users). We hope this work will help a larger community to get into the multiscale modeling world.

Finally, we show a complete rewrite of @MRuscone
cancer invasion model, removing most of the C++ code, and replacing it with the new mapping system. A larger scale, real-world example of how to use the latest #PhysiBoSS functionalities!

Third example had to be an immune example, since this is the most important application for #PhysiBoSS! We describe DCs, attracted by the CCL21 gradient toward the lymph node. There, they activate naive T-cells which differentiate in TH1,TH17 and Tregs (model from Corral et al.).

The second has been one of our goals with #PhysiBoSS for a long time: a signaling-controlled cell cycle model. Using the #Boolean model from Sizek et al., we link the cyclins to the transitions of the phases of the cell cycle. With that, we can reproduce the effect of mutants!

The first example is inspired by the TNF example of the original #PhysiBoSS. It shows how to quickly map a substrate concentration to a Boolean input, and an output to #PhysiCell's apoptosis and necrosis. It simulates long vs pulsatile treatment, necrotic core, and clonality!

In this tutorial, the user only needs to use #PhysiCell studio to build, parametrize, simulate and explore the simulation results! We implemented full PhysiBoSS compatibility in the studio, so that you can add your signaling model, and explore the #Boolean state of every cell in the results !

Many thanks to Marco Ruscone and Laurence Calzone for all their work that went into this tutorial, and to Andrea Checcoli, Randy Heiland, Emmanuel Barillot, and @mathcancer.bsky.social for helping us build, test, write, and review everything! Feedback welcome !

To conclude, this tutorial shows that #PhysiBoSS modeling doesn't require C++ coding skills, and is now simpler thanks to #PhysiCell Studio (even for advanced users). We hope this work will help a larger community to get into the multiscale modeling world.

Finally, we show a complete rewrite of @MRuscone
cancer invasion model, removing most of the C++ code, and replacing it with the new mapping system. A larger scale, real-world example of how to use the latest #PhysiBoSS functionalities!

Third example had to be an immune example, since this is the most important application for #PhysiBoSS! We describe DCs, attracted by the CCL21 gradient toward the lymph node. There, they activate naive T-cells which differentiate in TH1,TH17 and Tregs (model from Corral et al.).

The second has been one of our goals with #PhysiBoSS for a long time: a signaling-controlled cell cycle model. Using the #Boolean model from Sizek et al., we link the cyclins to the transitions of the phases of the cell cycle. With that, we can reproduce the effect of mutants!